More Certainty in Credit and Collections

CertainTeed used predictive analytics to transform A/R, freeing up working capital and enhancing customer service.

CIP logo 4 - CertainTeedA few years ago, the U.S. housing bubble burst and the construction industry tanked, which was challenging for every business in that sector. Valley Forge, Pennsylvania-based building-products manufacturer CertainTeed Corporation found itself at a crossroads. A subsidiary of Saint-Gobain, a global manufacturer with around 200,000 employees worldwide, the company faced a crucial decision: How could it continue selling in a distressed market while ensuring that its receivables would continue to be paid?

Treasury & Risk spoke with Susan Delloiacono, the company’s director of credit services, about how CertainTeed began using predictive analytics within its credit-and-collections automation system to identify exactly which customers pose the most credit risk. By basing decisions on more precise information, the company was able to streamline credit decisions and dramatically improve prioritization of receivables within the collections process. Now its accounts receivable (A/R) metrics are outstanding, and employees, customers, and the company are all thrilled with the change.

T&R:  Where did you start?

SD:  We started by implementing a new software system, AvantGard GETPAID from SunGard. We created a risk score that indicates each customer’s overall credit and collection risk to CertainTeed. The score includes whether they have a bank line of credit, which is critical for us. It includes a few Dun & Bradstreet metrics that reflect how they’re paying other vendors. And then the biggest element of the scorecard is how they pay CertainTeed—not how they are paying their electric bill, but how they are paying us. I’ve found that the Dun & Bradstreet information, on its own, can be woefully deficient. I had one customer that was in a technical bankruptcy, but their Dun & Bradstreet PAYDEX was still 80.

When our collectors look at their portfolio, it’s clear which customers they should attack first. We’re re-scoring our customers on a monthly basis, and when the score shows they are a high risk, they show up at the top of the collector’s list. It doesn’t matter how they did on last month’s score. If you’re at the top of the list right now, you’re going to be hearing from us every couple of days.

 

On the flip side, we can also classify overpayments. We had an example recently of a contractor that sent us a $20,000 check. Since our cash application had no open invoice to apply it to, the payment became a problem “overpayment” in the system. We looked into it and found that it was a remittance for an invoice that was two years old, which had already been paid. A collection analyst called the customer and alerted her accounts payable contact of the situation. She was so grateful! It was an error on their part, so we immediately returned the money. Through that process, the customer saw that we’ve got her back, and our analyst was able to develop a deeper, trusting relationship with that customer.

020514_CertainTeed_PQ2One other benefit I should point out is that we’ve also seen a dramatic improvement in terms of employee satisfaction. Now our staff knows that every transaction that appears in their collection queue is meaningful. We no longer have situations where our analysts complain, ‘We know our customer’s pay cycle is on Friday, but the system alerted us to call them on Thursday. The customers are annoyed with us, and we’re spending time following up needlessly.’ Our employees want to add value in every interaction they have with a customer. Now they really do.

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